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Simple and beautiful Analysis of an E-Commerce store data using Python, Numpy, Pandas, Matplotlib and Seaborn.

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Sajjad-Qureshi/E-Commerce-Sales-Analysis

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E-Commerce-Sales-Analysis

Project Purpose/Objective:

The purpose of this project is to Analysis an E-Commerce dataset provided by "The UCI Machine Learning Repository", extract meaning and answer some awesome business questions and show some awesome sales trends.

Methods used:

  • Data Cleaning
  • Data Manipulation
  • Data Exploration
  • Data Visualization

Tools & Technologies:

  • Descriptive Statistics
  • Python
  • Numpy, Pandas
  • Matplotlib
  • Jupyter Notebook

Project Description:

This repo contains data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for Analysis for a UK-based and registered non-store online retail. The company mainly sells unique all-occasion gifts, Many customers of the company are wholesalers. Now everybody has their own way of approaching any problem, for Data Analyst their main problem/task is to extract meaning from data and present/visualize it in such an easy and beautiful way for others to understand. I've divided this project in 4 main parts for easy and better understanding of Problem/Analysis.

  • Loading Dataset
  • Data Cleaning
  • Adding some Necessary Columns
  • Data Exploration (Most Important)

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Simple and beautiful Analysis of an E-Commerce store data using Python, Numpy, Pandas, Matplotlib and Seaborn.

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